A Comparative Study of Activated Carbons from Liquid to Solid Polymer Electrolytes for Electrochemical Capacitors
Bibliographic record
Abstract
A systematic study on the key factors affecting the performance of electrochemical capacitor electrodes in solid electrolytes and their liquid electrolyte baselines was conducted. The study combined a test matrix of two types of activate carbons (AC) with different specific surface area, pore size and structures at various loadings in three solid and liquid electrolyte pairs. Working curves on loading vs. capacitance of these ACs in solid and corresponding liquid electrolytes revealed the correlation and interconnection of these material properties. A cross-sectional microscopic elemental analysis was used to identify and visualize the influence of these factors. When transition from liquid to solid polymer electrolytes, the infiltration of the electrolyte into the porous carbon plays a critical role in the performance of AC electrode especially at a high loading. When the precursor solution of polymer electrolyte was relatively less viscous, AC with an open structure and mesopores had similar capacitance as their liquid counterparts. A highly viscous precursor solution blocked some access of the polymer electrolytes into the bulk electrode, making infiltration less effective at high loading. This work shows an approach to project the performance of carbon electrodes in solid electrolytes and can provide directions for developing solid-state electrochemical capacitors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".